Agentic modeling is shaping the future of GenAI

The advent of generative AI (GenAI) has been a milestone in the evolution of AI-driven technologies.  

Unlike narrow AI, which is tailored to specific tasks, GenAI systems can perform an array of intellectual tasks similar to those a human can undertake – like analyzing data, writing and illustrating. Within this broad spectrum of GenAI, agentic modeling has emerged as a specialized area focused on developing autonomous agents that can act on behalf of humans.

It involves creating systems that process data and perform predefined operations, with some level of autonomy in decision-making. These systems learn from interactions with their environment, adapt to new situations and make choices that align with their programmed goals or objectives.  

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GenAI on the corporate agenda

Organizations across industries are now incorporating GenAI into their strategic planning. A common business goal is to use these tools to simplify complex processes and enhance digital capabilities to improve the customer experience (CX) – and boost customer retention.

More than 90% of organizations agree that improvements in CX and employee experience will directly affect their net profit, according to NTT DATA’s 2023 Global Customer Experience Report.

At the same time, 64% of organizations believe that AI will boost their overall productivity, a Forbes Advisor survey found. This illustrates rising confidence in AI’s potential to transform business operations.

The GenAI market is responding to the need for platforms that meet these requirements by developing models tailored to industry-specific requirements.

This is contributing to exponential growth in the market. According to an IDC forecast, spending on GenAI – including software, hardware, and IT and business services – is expected to reach US$151.1 billion in 2027, with a compound annual growth rate of 86.1% between 2023 and 2027.

Agentic modeling: a pathway to artificial general intelligence

In this context, the interactive agent foundation model is a framework for AI systems that can interact effectively with humans or other virtual agents in a dynamic environment. These models provide a base for more complex functions that let AI agents understand and respond to inputs, make decisions and take contextually appropriate actions.

In customer service, for example, agentic models can gather data from multiple sources and provide real-time assistance to both human agents and customers during customer interactions, thereby helping human agents make better decisions and improving customer service.

Process-aware agentic models in business operations can employ GenAI capabilities to improve the employee experience, facilitate task completion and streamline workflows.

How agentic modeling is being applied

The interactive agent foundation model is a step toward artificial general intelligence, an advanced type of AI that would be able to reason, plan, solve problems, think abstractly, comprehend complex ideas and learn quickly from experience.

The foundation model’s adaptability and versatility hold promise for applications in several domains, such as robotics, gaming and healthcare. Once agents can interpret textual instructions and act in a simulated environment, the model supports the development of intelligent robotics and virtual assistants that can comprehend and carry out complex directives in any industry.

As part of Microsoft’s AI for Good initiative, agentic models are being used to autonomously analyze data, predict outcomes and make informed decisions to advance goals in sustainability, health, humanitarian aid and social justice.

Move forward responsibly

However, these developments also raise questions about the ethics and implications of AI systems making decisions that can affect humans and their environment.

These concerns underscore the importance of working with expert service providers to implement smart, AI-driven solutions safely and securely.

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The start of a new cycle of innovation

Advancements in GenAI and agentic modeling are set to revolutionize the technological landscape, offering unprecedented levels of autonomy and adaptability.

These technologies are not only enhancing organizations’ current capabilities. They’re also paving the way for innovations that will redefine AI’s potential to drive progress and create value – if it’s used responsibly and ethically, with a deep understanding of the risks involved and how to manage them.